Light-induced insulator-metal transition in Sr2IrO4 reveals the nature of the insulating ground state.

Sr2IrO4 has attracted considerable attention due to its structural and electronic similarities to La2CuO4, the parent compound of high-Tc superconducting cuprates. It was proposed as a strong spin-orbit-coupled Jeff = 1/2 Mott insulator, but the Mott nature of its insulating ground state has not been conclusively established. Here, we use ultrafast laser pulses to realize an insulator-metal transition in Sr2IrO4 and probe the resulting dynamics using time- and angle-resolved photoemission spectroscopy. We observe a gap closure and the formation of weakly renormalized electronic bands in the gap region. Comparing these observations to the expected temperature and doping evolution of Mott gaps and Hubbard bands provides clear evidence that the insulating state does not originate from Mott correlations. We instead propose a correlated band insulator picture, where antiferromagnetic correlations play a key role in the gap opening. More broadly, our results demonstrate that energy-momentum-resolved nonequilibrium dynamics can be used to clarify the nature of equilibrium states in correlated materials.

Quantum Optics Measurement Scheme for Quantum Geometry and Topological Invariants.

We show how a quantum optical measurement scheme based on heterodyne detection can be used to explore geometrical and topological properties of condensed matter systems. Considering a 2D material placed in a cavity with a coupling to the environment, we compute correlation functions of the photons exiting the cavity and relate them to the hybrid light-matter state within the cavity. Different polarizations of the intracavity field give access to all components of the quantum geometric tensor on contours in the Brillouin zone defined by the transition energy. Combining recent results based on the metric-curvature correspondence with the measured quantum metric allows us to characterize the topological phase of the material. Moreover, in systems where S_{z} is a good quantum number, the procedure also allows us to extract the spin Chern number. As an interesting application, we consider a minimal model for twisted bilayer graphene at the magic angle, and discuss the feasibility of extracting the Euler number.

Correlated Electronic Structure of La_{3}Ni_{2}O_{7} under Pressure.

Recently, superconductivity with a T_{c} up to 78 K has been reported in bulk samples of the bilayer nickelate La_{3}Ni_{2}O_{7} at pressures above 14 GPa. Important theoretical tasks are the formulation of relevant low-energy models and the clarification of the normal state properties. Here, we study the correlated electronic structure of the high-pressure phase in a four-orbital low-energy subspace using different many-body approaches: GW, dynamical mean field theory (DMFT), extended DMFT (EDMFT) and GW+EDMFT, with realistic frequency-dependent interaction parameters. The nonlocal correlation and screening effects captured by GW+EDMFT result in an instability toward the formation of charge stripes, with the 3d_{z^{2}} as the main active orbital. We also comment on the potential relevance of the rare-earth self-doping pocket, since hole doping suppresses the ordering tendency.

Vertex-Based Diagrammatic Treatment of Light-Matter-Coupled Systems.

We propose a diagrammatic Monte Carlo approach for quantum impurity models, which can be regarded as a generalization of the strong-coupling expansion for fermionic impurity models. The algorithm is based on a self-consistently computed three-point vertex and a stochastically sampled four-point vertex, and it allows one to obtain numerically exact results in a wide parameter regime. The performance of the algorithm is demonstrated with applications to a spin-boson model representing an emitter in a waveguide. As a function of the coupling strength, the spin exhibits a delocalization-localization crossover at low temperatures, signaling a qualitative change in the real-time relaxation. In certain parameter regimes, the response functions of the emitter coupled to the electromagnetic continuum can be described by an effective Rabi model with appropriately defined parameters. We also discuss the spatial distribution of the photon density around the emitter.

Spin, Charge, and η-Spin Separation in One-Dimensional Photodoped Mott Insulators.

We show that effectively cold metastable states in one-dimensional photodoped Mott insulators described by the extended Hubbard model exhibit spin, charge, and η-spin separation. Their wave functions in the large on-site Coulomb interaction limit can be expressed as |Ψ⟩=|Ψ_{charge}⟩|Ψ_{spin}⟩|Ψ_{η-spin}⟩, which is analogous to the Ogata-Shiba states of the doped Hubbard model in equilibrium. Here, the η-spin represents the type of photo-generated pseudoparticles (doublon or holon). |Ψ_{charge}⟩ is determined by spinless free fermions, |Ψ_{spin}⟩ by the isotropic Heisenberg model in the squeezed spin space, and |Ψ_{η-spin}⟩ by the XXZ model in the squeezed η-spin space. In particular, the metastable η-pairing and charge-density-wave (CDW) states correspond to the gapless and gapful states of the XXZ model. The specific form of the wave function allows us to accurately determine the exponents of correlation functions. The form also suggests that the central charge of the η-pairing state is 3 and that of the CDW phase is 2, which we numerically confirm. Our study provides analytic and intuitive insights into the correlations between active degrees of freedom in photodoped strongly correlated systems.

Doping Asymmetry and Layer-Selective Metal-Insulator Transition in Trilayer K_{3+x}C_{60}.

Thin films provide a versatile platform to tune electron correlations and explore new physics in strongly correlated materials. Epitaxially grown thin films of the alkali-doped fulleride K_{3+x}C_{60}, for example, exhibit intriguing phenomena, including Mott transitions and superconductivity, depending on dimensionality and doping. Surprisingly, in the trilayer case, a strong electron-hole doping asymmetry has been observed in the superconducting phase, which is absent in the three-dimensional bulk limit. Using density-functional theory plus dynamical mean-field theory, we show that this doping asymmetry results from a substantial charge reshuffling from the top layer to the middle layer. While the nominal filling per fullerene is close to n=3, the top layer rapidly switches to an n=2 insulating state upon hole doping, which implies a doping asymmetry of the superconducting gap. The interlayer charge transfer and layer-selective metal-insulator transition result from the interplay between crystal field splittings, strong Coulomb interactions, and an effectively negative Hund coupling. This peculiar charge reshuffling is absent in the monolayer system, which is an n=3 Mott insulator, as expected from the nominal filling.

Anomalous Temperature Dependence of High-Harmonic Generation in Mott Insulators.

We reveal the crucial effect of strong spin-charge coupling on high-harmonic generation (HHG) in Mott insulators. In a system with antiferromagnetic correlations, the HHG signal is drastically enhanced with decreasing temperature, even though the gap increases and the production of charge carriers is suppressed. This anomalous behavior, which has also been observed in recent HHG experiments on Ca_{2}RuO_{4}, originates from a cooperative effect between the spin-charge coupling and the thermal ensemble, as well as the strongly temperature-dependent coherence between charge carriers. We argue that the peculiar temperature dependence of HHG is a generic feature of Mott insulators, which can be controlled via the Coulomb interaction and dimensionality of the system. Our results demonstrate that correlations between different degrees of freedom, which are a characteristic feature of strongly correlated solids, have significant and nontrivial effects on nonlinear optical responses.

Mott versus Hybridization Gap in the Low-Temperature Phase of 1T-TaS_{2}.

We address the long-standing problem of the ground state of 1T-TaS_{2} by computing the correlated electronic structure of stacked bilayers using the GW+EDMFT method. Depending on the surface termination, the semi-infinite uncorrelated system is either band insulating or exhibits a metallic surface state. For realistic values of the on-site and inter-site interactions, a Mott gap opens in the surface state, but it is smaller than the gap originating from the bilayer structure. Our results are consistent with recent scanning tunneling spectroscopy measurements for different terminating layers, and with our own photoemission measurements, which indicate the coexistence of spatial regions with different gaps in the electronic spectrum. By comparison to exact diagonalization data, we clarify the interplay between Mott insulating and band insulating behavior in this archetypal layered system.

An Automatic System for Continuous Pain Intensity Monitoring Based on Analyzing Data from Uni-, Bi-, and Multi-Modality.

Pain is a reliable indicator of health issues; it affects patients' quality of life when not well managed. The current methods in the clinical application undergo biases and errors; moreover, such methods do not facilitate continuous pain monitoring. For this purpose, the recent methodologies in automatic pain assessment were introduced, which demonstrated the possibility for objectively and robustly measuring and monitoring pain when using behavioral cues and physiological signals. This paper focuses on introducing a reliable automatic system for continuous monitoring of pain intensity by analyzing behavioral cues, such as facial expressions and audio, and physiological signals, such as electrocardiogram (ECG), electromyogram (EMG), and electrodermal activity (EDA) from the X-ITE Pain Dataset. Several experiments were conducted with 11 datasets regarding classification and regression; these datasets were obtained from the database to reduce the impact of the imbalanced database problem. With each single modality (Uni-modality) experiment, we used a Random Forest [RF] baseline method, a Long Short-Term Memory (LSTM) method, and a LSTM using a sample weighting method (called LSTM-SW). Further, LSTM and LSTM-SW were used with fused modalities (two modalities = Bi-modality and all modalities = Multi-modality) experiments. Sample weighting was used to downweight misclassified samples during training to improve the performance. The experiments' results confirmed that regression is better than classification with imbalanced datasets, EDA is the best single modality, and fused modalities improved the performance significantly over the single modality in 10 out of 11 datasets.

A Baseline for Cross-Database 3D Human Pose Estimation.

Vision-based 3D human pose estimation approaches are typically evaluated on datasets that are limited in diversity regarding many factors, e.g., subjects, poses, cameras, and lighting. However, for real-life applications, it would be desirable to create systems that work under arbitrary conditions ("in-the-wild"). To advance towards this goal, we investigated the commonly used datasets HumanEva-I, Human3.6M, and Panoptic Studio, discussed their biases (that is, their limitations in diversity), and illustrated them in cross-database experiments (for which we used a surrogate for roughly estimating in-the-wild performance). For this purpose, we first harmonized the differing skeleton joint definitions of the datasets, reducing the biases and systematic test errors in cross-database experiments. We further proposed a scale normalization method that significantly improved generalization across camera viewpoints, subjects, and datasets. In additional experiments, we investigated the effect of using more or less cameras, training with multiple datasets, applying a proposed anatomy-based pose validation step, and using OpenPose as the basis for the 3D pose estimation. The experimental results showed the usefulness of the joint harmonization, of the scale normalization, and of augmenting virtual cameras to significantly improve cross-database and in-database generalization. At the same time, the experiments showed that there were dataset biases that could not be compensated and call for new datasets covering more diversity. We discussed our results and promising directions for future work.

SFPD: Simultaneous Face and Person Detection in Real-Time for Human-Robot Interaction.

Face and person detection are important tasks in computer vision, as they represent the first component in many recognition systems, such as face recognition, facial expression analysis, body pose estimation, face attribute detection, or human action recognition. Thereby, their detection rate and runtime are crucial for the performance of the overall system. In this paper, we combine both face and person detection in one framework with the goal of reaching a detection performance that is competitive to the state of the art of lightweight object-specific networks while maintaining real-time processing speed for both detection tasks together. In order to combine face and person detection in one network, we applied multi-task learning. The difficulty lies in the fact that no datasets are available that contain both face as well as person annotations. Since we did not have the resources to manually annotate the datasets, as it is very time-consuming and automatic generation of ground truths results in annotations of poor quality, we solve this issue algorithmically by applying a special training procedure and network architecture without the need of creating new labels. Our newly developed method called Simultaneous Face and Person Detection (SFPD) is able to detect persons and faces with 40 frames per second. Because of this good trade-off between detection performance and inference time, SFPD represents a useful and valuable real-time framework especially for a multitude of real-world applications such as, e.g., human-robot interaction.

Automatic vs. Human Recognition of Pain Intensity from Facial Expression on the X-ITE Pain Database.

Prior work on automated methods demonstrated that it is possible to recognize pain intensity from frontal faces in videos, while there is an assumption that humans are very adept at this task compared to machines. In this paper, we investigate whether such an assumption is correct by comparing the results achieved by two human observers with the results achieved by a Random Forest classifier (RFc) baseline model (called RFc-BL) and by three proposed automated models. The first proposed model is a Random Forest classifying descriptors of Action Unit (AU) time series; the second is a modified MobileNetV2 CNN classifying face images that combine three points in time; and the third is a custom deep network combining two CNN branches using the same input as for MobileNetV2 plus knowledge of the RFc. We conduct experiments with X-ITE phasic pain database, which comprises videotaped responses to heat and electrical pain stimuli, each of three intensities. Distinguishing these six stimulation types plus no stimulation was the main 7-class classification task for the human observers and automated approaches. Further, we conducted reduced 5-class and 3-class classification experiments, applied Multi-task learning, and a newly suggested sample weighting method. Experimental results show that the pain assessments of the human observers are significantly better than guessing and perform better than the automatic baseline approach (RFc-BL) by about 1%; however, the human performance is quite poor due to the challenge that pain that is ethically allowed to be induced in experimental studies often does not show up in facial reaction. We discovered that downweighting those samples during training improves the performance for all samples. The proposed RFc and two-CNNs models (using the proposed sample weighting) significantly outperformed the human observer by about 6% and 7%, respectively.

Quantum Simulation Meets Nonequilibrium Dynamical Mean-Field Theory: Exploring the Periodically Driven, Strongly Correlated Fermi-Hubbard Model.

We perform an ab initio comparison between nonequilibrium dynamical mean-field theory and optical lattice experiments by studying the time evolution of double occupations in the periodically driven Fermi-Hubbard model. For off-resonant driving, the range of validity of a description in terms of an effective static Hamiltonian is determined and its breakdown due to energy absorption close to resonance is demonstrated. For near-resonant driving, we investigate the response to a change in driving amplitude and discover an asymmetric excitation spectrum with respect to the detuning. In general, we find good agreement between experiment and theory, which cross validates the experimental and numerical approaches in a strongly correlated nonequilibrium system.

Predicting Group Contribution Behaviour in a Public Goods Game from Face-to-Face Communication.

Experimental economic laboratories run many studies to test theoretical predictions with actual human behaviour, including public goods games. With this experiment, participants in a group have the option to invest money in a public account or to keep it. All the invested money is multiplied and then evenly distributed. This structure incentivizes free riding, resulting in contributions to the public goods declining over time. Face-to-face Communication (FFC) diminishes free riding and thus positively affects contribution behaviour, but the question of how has remained mostly unknown. In this paper, we investigate two communication channels, aiming to explain what promotes cooperation and discourages free riding. Firstly, the facial expressions of the group in the 3-minute FFC videos are automatically analysed to predict the group behaviour towards the end of the game. The proposed automatic facial expressions analysis approach uses a new group activity descriptor and utilises random forest classification. Secondly, the contents of FFC are investigated by categorising strategy-relevant topics and using meta-data. The results show that it is possible to predict whether the group will fully contribute to the end of the games based on facial expression data from three minutes of FFC, but deeper understanding requires a larger dataset. Facial expression analysis and content analysis found that FFC and talking until the very end had a significant, positive effect on the contributions.

High-Harmonic Generation in Mott Insulators.

Using Floquet dynamical mean-field theory, we study the high-harmonic generation in the time-periodic steady states of wide-gap Mott insulators under ac driving. In the strong-field regime, the harmonic intensity exhibits multiple plateaus, whose cutoff energies ε_{cut}=U+mE_{0} scale with the Coulomb interaction U and the maximum field strength E_{0}. In this regime, the created doublons and holons are localized because of the strong field and the mth plateau originates from the recombination of mth nearest-neighbor doublon-holon pairs. In the weak-field regime, there is only a single plateau in the intensity, which originates from the recombination of itinerant doublons and holons. Here, ε_{cut}=Δ_{gap}+αE_{0}, with Δ_{gap} the band gap and α>1. We demonstrate that the Mott insulator shows a stronger high-harmonic intensity than a semiconductor model with the same dispersion as the Mott insulator, even if the semiconductor bands are broadened by impurity scattering to mimic the incoherent scattering in the Mott insulator.

Spontaneous Orbital-Selective Mott Transitions and the Jahn-Teller Metal of A_{3}C_{60}.

The alkali-doped fullerides A_{3}C_{60} are half-filled three-orbital Hubbard systems which exhibit an unconventional superconducting phase next to a Mott insulator. While the pairing is understood to arise from an effectively negative Hund coupling, the highly unusual Jahn-Teller metal near the Mott transition, featuring both localized and itinerant electrons, has not been understood. This property is consistently explained by a previously unrecognized phenomenon: the spontaneous transition of multiorbital systems with negative Hund coupling into an orbital-selective Mott state. This symmetry-broken state, which has no ordinary orbital moment, is characterized by an orbital-dependent two-body operator (the double occupancy) or an orbital-dependent kinetic energy and may be regarded as a diagonal-order version of odd-frequency superconductivity. We propose that the recently discovered Jahn-Teller metal phase of Rb_{x}Cs_{3-x}C_{60} is an experimental realization of this novel state of matter.

J Freezing and Hund's Rules in Spin-Orbit-Coupled Multiorbital Hubbard Models.

We investigate the phase diagram of the spin-orbit-coupled three orbital Hubbard model at arbitrary filling by means of dynamical mean-field theory combined with the continuous-time quantum Monte Carlo method. We find that the spin-freezing crossover occurring in the metallic phase of the nonrelativistic multiorbital Hubbard model can be generalized to a J-freezing crossover, with J=L+S, in the spin-orbit-coupled case. In the J-frozen regime the correlated electrons exhibit a nontrivial flavor selectivity and energy dependence. Furthermore, in the regions near n=2 and n=4 the metallic states are qualitatively different from each other, which reflects the atomic Hund's third rule. Finally, we explore the appearance of magnetic order from exciton condensation at n=4 and discuss the relevance of our results for real materials.

Photoinduced Enhancement of Excitonic Order.

We study the dynamics of excitonic insulators coupled to phonons using the time-dependent mean-field theory. Without phonon couplings, the linear response is given by the damped amplitude oscillations of the order parameter with a frequency equal to the minimum band gap. A phonon coupling to the interband transfer integral induces two types of long-lived collective oscillations of the amplitude, one originating from the phonon dynamics and the other from the phase mode, which becomes massive. We show that, even for small phonon coupling, a photoinduced enhancement of the exciton condensation and the gap can be realized. Using the Anderson pseudospin picture, we argue that the origin of the enhancement is a cooperative effect of the massive phase mode and the Hartree shift induced by the photoexcitation. We also discuss how the enhancement of the order and the collective modes can be observed with time-resolved photoemission spectroscopy.

Nonequilibrium GW+EDMFT: Antiscreening and Inverted Populations from Nonlocal Correlations.

We study the dynamics of screening in photodoped Mott insulators with long-ranged interactions using a nonequilibrium implementation of the GW plus extended dynamical mean-field theory formalism. Our study demonstrates that the complex interplay of the injected carriers with bosonic degrees of freedom (charge fluctuations) can result in long-lived transient states with properties that are distinctly different from those of thermal equilibrium states. Systems with strong nonlocal interactions are found to exhibit a self-sustained population inversion of the doublons and holes. This population inversion leads to low-energy antiscreening which can be detected in time-resolved electron-energy-loss spectra.

Ultrafast Electronic Band Gap Control in an Excitonic Insulator.

We report on the nonequilibrium dynamics of the electronic structure of the layered semiconductor Ta_{2}NiSe_{5} investigated by time- and angle-resolved photoelectron spectroscopy. We show that below the critical excitation density of F_{C}=0.2 mJ cm^{-2}, the band gap narrows transiently, while it is enhanced above F_{C}. Hartree-Fock calculations reveal that this effect can be explained by the presence of the low-temperature excitonic insulator phase of Ta_{2}NiSe_{5}, whose order parameter is connected to the gap size. This work demonstrates the ability to manipulate the band gap of Ta_{2}NiSe_{5} with light on the femtosecond time scale.